A neural network-based technique for change detection of linear features and its application to a Mediterranean Region

Idan Feldberg, Nathan S. Netanyahu, Maxim Shoshany

Research output: Contribution to journalArticlepeer-review

Abstract

An Artificial Neural Network (ANN) for change detection from multi-temporal satellite images, which was reported in [6], has been further developed and tested, as part of a study of an area of high spatio-temporal heterogeneity along a climatic gradient between humid and arid climate regions. Four recognition classes, "positive change", "negative change", "false change", and "no change" were learned by a backpropagation feedforward ANN and then applied to Landsat images that were acquired over the study area in 1992 and 1997. A comparison with existing classification techniques indicates, in many instances, significantly improved performance due to the ANN developed.
Original languageEnglish
JournalInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2
StatePublished - 1 Jan 2002

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